Models play a key role in environmental research but who should develop them has been the subject of much debate between vendors in the private sector and government scientists and engineers. The debate is about whether the models should be developed by private organizations and kept as proprietary or should federal funding be used for model development and the final product is used and applied as a public model. Over the past century in the United States, basic research was primarily funded by the government.
As with basic research, federal funding is required for model development as public models build trust and give confidence to the regulated parties and other interested individuals and groups. Most of U.S. basic research is conducted at higher education institutions and is funded by the federal government.
There is a continuing debate in the United States among vendors, users, and Federals agencies about the role of government in funding basic research in general and computational model development in particular, specifically, public domain vs.
proprietary models. The debate stems from the fact that the government funds model development when the same can be done by the private sector. Some see this as government competing against the private sector, a view which is not shared by others who propose that government should continue funding model development. The fundamental question is, should the government be involved in funding research and development (R&D) activities of which computational modeling is one part. This paper describes historical trends in environmental model development an integral component of R&D, in the United States and the reasons for funding model development by the U.
S. government agencies.
Throughout the ages, multiple discoveries and explorations were achieved with the financial help from monarchs and rich. Galileo’s education at the University of Pisa, founded by Pope Clement VI was instrumental with his revelation that the Earth revolves around the sun. Later on, German universities adopted the notion that it was the academy’s responsibility to advance the understanding of science Jahnke, 2018). Spanish monarchs Ferdinand of Aragon and Isabella of Castile funded Christopher Columbus discovery voyage (History, 2009). The British government funded Darwin’s Beagle voyage in the 19th century. In the 1870s, Alexander Graham Bell received much of the needed money to develop his “harmonic telegraph,” from the wealthy father of one of his students, 16-year-old Mabel Hubbard. He even borrowed money from his assistant, Thomas Watson (LOC, 2018).
In the U.S., Federal support for research began eleven years after the signing of the Constitution. On July 16, 1798, the Marine Hospital Service was established by President John Adams (Haney, 2014). In 1887, a one-room lab was set up at the Marine Hospital on Staten Island, NY which was renamed the Hygenic Laboratory in 1891, when it was relocated to Washington DC, and currently known as the National Institutes of Health (NIH) (Lugi, 2011). In 1918 the Chamberlain-Kahn Act authorized grants to 25 institutions. This act set the precedent for the federal government grants to university scientists to fund their research (the NIH Almanac, 2016). Science and technology research at American universities was historically funded by local industry, philanthropy, and universities themselves (David Kaiser, 2011). In 1919 that funding model moved in the direction of the industry when MIT created a division of industrial cooperation and research. This model worked well until the stock market crashed in 1929. The crash took away 60 percent of the budgets for some departments and also stanched the flow of funding from foundations (Kaiser, 2011). In 1931, total grants from American foundations amounted to $52.5 million. Three years later the figure was $34 million, and as late as 1940 it was $10 million less than it had been in 1931 (Neal et al, 2008).
Before World War II, government money for research was rare and was mostly aimed at aeronautics and agriculture studies. In 1940 President Franklin Delano Roosevelt created the National Defense Research Committee, which evolved into the Office of Scientific Research and Development (OSRD). OSRD’s projects included wartime research on a variety of topics, from radar to malaria, as well as the Manhattan Project. President Roosevelt placed OSRD under the chairmanship of Vannevar Bush, a former MIT vice president and dean and president of the Carnegie Institute to design an apparatus that could fund science in the postwar years. Bush wrote the historic report “Science: the endless frontier.” which became famous as the prescription for government support of science (Bush, 1945). In 1950, President Harry Truman created the National Science Foundation (NSF), charging it with developing a national policy for the promotion of basic research. Since then the federal funding for R&D flowed with gradually increasing velocity.
Federally funded research addresses many national objectives and provides extraordinary benefits to society through the creation of new knowledge (OTA, 1991). As illustrated in figure 1 (OECD 2018), the United States is a world leader in R&D funding, funding as much as 69% of annual global R&D in the period following World War II (Mitchell, 1997).
Basic research is defined as experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundations of phenomena and observable facts. Basic research may include activities with broad or general applications in mind but should exclude research directed towards a specific application or requirement. Applied research is defined as the original investigation undertaken in order to acquire new knowledge. Applied research is, however, directed primarily towards a specific practical aim or objective. (Sargent, 2018).
R&D in the United States is funded and performed by a number of sectors—including the federal government, state governments, businesses, academia, and nonprofit organizations—for a variety of purposes. Business and the federal government—have accounted for more than 90% of U.S. R&D funding since 1953 (Sargent, 2018) and the federal government is the main funding authority for basic research. Figure 2 (Data from NSF, 2018) shows historical trends in the R&D spending.
Computational models are important for R&D as they have been used to explain scientific phenomena and predicting outcomes where empirical observations are limited or unavailable (Ambrose et al, 2009). Environmental models play an important role in the environmental field as the spatial and temporal scales of environmental processes cannot be analyzed with monitoring data alone because of time and resource constraints. Models help in making the linkage between economic activity and environment. Environmental modeling has a relatively long history in the United States. Model development was based on computing power, faster computer led to the development of complex and multi-dimensional models. Advances in computer hardware and software technology (mainframe, mini-computer, micro-computer, desktop, laptop, model integration, and Artificial Intelligence, Machine Learning, imagery, and remote sensing) revolutionized model development and application. Increasingly available computational power has led to the development of complex hydrologic models. The Model complexity (analytical models, screening models, 1-, 2-, 3-dimension, multi-phase, multicomponent, multi-species, chemically reactive, real-time, etc.) increases with the computer power and the problems to which they are applied. Faster computers have promoted dynamic, spatially-detailed models which use specialized user interface for linkage with other models and databases. There are a number of different kinds of model: Empirical, Mechanistic, Deterministic, Probabilistic, Dynamic, and Static.
Since the early 19th century, the nation’s water policies have evolved from emphasizing navigation and settlement, to emphasizing physical development of water supplies to ameliorate scarcity, and finally to emphasizing the protection and enhancement of the environment. Government-funded research on water resources has positively impacted the nation. This research falls into two categories: to facilitate and enhance the solving of water and water management problems; and to develop the scientific knowledge necessary to undergird mandated regulatory programs (NRC, 2004). The State Water Resources Research Institute Program and a national program in water resources research evolved from the Water Resources Research Act of 1964, as amended, the Water Research and Development Act of 1978, Public Law 96-457, and the Water Research and Development Act of 1984. The federal water research funding programs – Office of Water Resources Research (OWRR) in 1964-1974 and Office of Water Research & Technology (OWRT) in 1974-1982 were very effective in sponsoring model development (Burton, 1984).
The primary regulatory driver for water quality modeling in the U.S. has been the 1956 Federal Water Pollution Control Act, including the Clean Water Act and its amendments (Ambrose, 2008). Since the 1970s when American environmental agencies and programs were created largely in the 1970s the federal government spends around $5 billion (figure 3) each year for environmental research and development programs. Over 20 federal departments’ and agencies provide funds for environmental research and development through hundreds of programs.
Funding for environmental R&D funding is steady but its percentage share of the total federal R&D funding keeps shrinking (figure 4) over years. This figure illustrates the decline in funding for the environment from 10% in 1970 to 5% in 2017.
In the last two decade, there has been a vast increase in the number, variety, and complexity of environmental models available regulatory purposes. Demand for models expanded as the participants in regulatory processes, Congress, U.S. Environmental Protection Agency (EPA), Office of Management and Budget (OMB), stakeholders, and the general public required improved analysis of environmental issues and the consequences of proposed regulations. Demands for models increased as policymakers have attempted to with the improvement in the ability of environmental regulatory activities to achieve the desired environmental benefits and reduce implementation costs (NRC, 2007). The use of models has resulted in great advances in scientific understanding, knowledge, and improvements in the environmental field.
Demands for models increased to achieve the desired environmental benefits and reduce implementation costs of environmental regulatory activities.
Environmental models are critical to regulatory decision making and help guide research, policies making, and regulatory compliance. Modeling provides data for decision makers who need to consider many competing objectives. Federal agencies reliance on models has only increased over time. A number of federal programs make decisions based on information from environmental models by simulating different processes, including natural systems (chemical, physical, and biological) and economic phenomena. This is accomplished by using economic, behavioral, physical, engineering design, health, ecological, and fate/transport models (EPA, 2009). There are three categories of regulatory models: Policy analysis models affect national policy decisions; National regulatory decision-making models inform national regulatory decision making after the overall policy has been established and implementation applications. Many regulations issued by the EPA are based on results from models.
Models also have useful applications outside the regulatory context. For example, because models include explicit mathematical statements about system mechanics, they serve as research tools for exploring new scientific issues and screening tools for simplifying and/or refining existing scientific paradigms or software (SAB 1993, 1989). Models also help in analyzing ecological systems, design field studies, interpret data, and generalize results (EPA, 2009).
Table 1 illustrates that while the EPA has been a leader in the broad development and use of water quality models, other federal and state agencies have made strong contributions to the field. Chief among these are NOAA, NWS (significant for hydrology, coastal, weather, ocean modeling), the U.S. Army Corps of Engineers’ Hydrologic Engineering Center (HEC) and Waterways Experiment Station, which have been longstanding leaders in hydrologic and water quality modeling. Other major contributors include the Tennessee Valley Authority, the National Oceanic and Atmospheric Administration, the U.S. Department of Agriculture, the U.S. Geologic Survey (USGS), and the U.S. Department of Energy.
EPA is a global leader in developing and applying models in the environmental regulatory decision process. Since its inception, EPA has been involved in the development and application of models for environmental regulatory purposes and its reliance on models has only increased over time. The use of models is central to the regulatory decision-making process because of prospective analyses of EPAs policies, including estimating possible future effects on the environment, human health, and the economy. The agency uses models to generate estimates/predictions) when data are not available and also uses models to analyze measurement data for trends and effects (NRC, 2007). A number of EPA programs make decisions based on information from environmental modeling applications. Within the Agency: models are used to simulate many different processes, including natural (chemical, physical, and biological) systems, economic phenomena, and decision processes; many types of models are employed, including economic, behavioral, physical, engineering design, health, ecological, and fate/transport models.
The USGS has always led the development of hydrologic and environmental models. These models are used for hydrologic investigations and to predict the fate and movement of solutes and contaminants in water (Barlow and Harbaugh, 2006), (Molz, 2017), and (Zhou and Li, 2011).
AWWA, 2017 summarized historical development in the modeling of drinking water distribution system. This development includes manual engineering calculations for small-pipe systems in the 1960s; development of modeling software with advanced functionalities (e.g. extended period simulation) from 1970-1990; exponential growth of distribution system modeling capabilities in 1990s including development of public domain distribution system EPANET by the EPA; development of Software packages to interface with GIS from 2000–2010; and at present with the integration of real-time data and sensors has expanded the uses and applications of models.
The Department of Energy (DOE) develops and applies high fidelity models in order to improve understanding of the significant drivers, feedbacks, and understanding the role of multi-sector interactions with the physical-human system, uncertainties through multiple programs The atmospheric-science program of the DOE environmental research is intended to understand contaminant flows in complex terrain for application in models used in emergency preparedness and emergency response. The subsurface-science program consists of Long-term basic research on physical, chemical, and biological mechanisms that control the mobilization, stability, and transport of chemicals in subsoils and groundwater; hydrogeology, including the hydraulic, microbiological, and geochemical properties of the subsurface that affect chemical mobility and stability; and the microbiology of deep sediments and groundwater.
NASA has one of the largest process-based environmental research programs in the federal government. This program seeks to provide the scientific underpinning and model development necessary to understand processes of global importance, such as the role of clouds in the earth’s energy budget and the role of carbon and nitrogen dynamics in deforestation and its consequences for atmospheric carbon dioxide. The research program helps to define the major scientific issues for which global measurements, and therefore satellite missions, are appropriate (NRC, 1993).
DOD’s environmental sciences R&D is oriented toward developing baseline data, remote sensing technologies, and predictive models of the ocean, local area conditions, and target environment characteristics. Environmental modeling at the DOD is led by the Hydrologic Engineering Center, Engineering Research and Development Center, Environmental Laboratory, and Coastal & Hydraulic Research Laboratory.
Hydrological and environmental models are being developed concurrently that utilize remote sensing data for input, calibration, and validation within a wide range of temporal and spatial contexts. Development of new models to meet the latest challenges is funded by the federal government.
Francis Bacon, in his Advancement of Learning, published in 1605 argued that governments had to fund science because no one else would. Vannevar Bush wrote a thorough justification for a strong governmental role in supporting research in the scientific community (Bush, 1950). His main argument that the responsibilities for promoting new scientific knowledge and for developing scientific talent were properly the concern of the federal government because these activities vitally affect the nation’s health, prosperity, and national security. He noted that the benefits of research were widespread and often appeared many years after the research was done.
“It is sometimes asked why the federal government should support research on water resources instead of leaving this activity to the private sector. The answer lies with the fact that the results of much water resources research, particularly basic research, have the characteristics of a public good. That is, once the research is concluded, the results should be freely available to any or all, irrespective of whether the recipients directly pay for them. Those who produce research with public good characteristics are unable to capture all of the returns to that research because the results are not patentable or licensable. Indeed, the private sector typically underinvests or fails to invest at all in the production of public goods because it cannot capture or ‘appropriate’ all of the returns from the investment. The problem of the lack of appropriability is especially pertinent to water resources since water is a publicly held resource. Although private firms and individuals may enjoy the right to use water, they rarely have title to the corpus or body of the resource. Lack of appropriability combined with public ownership of the resource makes the justification for public support of water resources research compelling (NRC, 2004).”
The use of proprietary models (any component that is a fundamental part of the model’s structure or functionality is not available for free to the general public) in the regulatory process can produce distrust among regulated parties and other interested individuals and groups because their use might prevent those affected by a regulatory decision from having access to a model that may have affected the decision.
“A primary policy justification for public investments in basic research and for incentives (e.g., tax credits) for the private sector to conduct research is the view, widely held by economists, that the private sector will be left on its own, underinvest in basic research from a societal perspective. The usual argument for this view is that the social returns (i.e., the benefits to society at large) exceed the private returns (i.e., the benefits accruing to the private investor, such as increased revenues or higher stock value). Other factors that may inhibit corporate investment in basic research include long time horizons for commercial applications (diminishing the potential returns due to the time value of money), high levels of technical risk/uncertainty, shareholder demands for shorter-term returns, and asymmetric and imperfect information (Sargent, 2018).”
Developers of proprietary models are motivated by profit from selling, updating and maintaining the model, and training users on the model. This proprietary model development may be advancing the science of modeling but their use is not always advocated by the environmental organization (Sass 2004) and a representative of a pro-business group advocating for regulatory reform (Slaughter 2004).
Without meaningful intellectual property protections, modelers would not have incentives to develop sophisticated models in the private sector. Environmental and industry groups (Sass 2004; Slaughter 2004) have argued against using proprietary models in the regulatory arena as proprietary models are directly at odds with the goals of open government and transparency.
Pew Research Center conducted a survey which concluded that about seven-in-ten adults say that “government investments in engineering and technology (72%) and in basic scientific research (71%) usually pay off in the long run. Some 61% say that government investment is essential for scientific progress, while 34% say private investment is enough to ensure scientific progress is made (Pew Research Center, 2015).
Models have a prominent future in the environmental decision-making process because their value clearly outweighs their inherent imperfections. The use of environmental regulatory models in the future will have to deal effectively with the vastly increased amounts of data, improvements in modeling methods and technologies, and changing the perspective on how best to use the results of models in the regulatory process (NRC, 2007). The use of proprietary models in the regulatory process can produce distrust among regulated parties and other interested individuals and groups because their use might prevent those affected by a regulatory decision from having access to a model that may have affected the decision. It can also introduce bias, for example, tobacco industry funding research into smoking and health effects.
The federal government has supported scientific research for the benefit of society and these investments have yielded manifest benefits that include computers, the Internet, wireless communication, the laser, the global positioning system, and modern medicine, among many others. These advances have enabled the United States to achieve unprecedented prosperity, security, and quality of life. Without government support, most basic scientific research will never happen. The United States remains at the forefront of R&D with the world’s largest investment in R&D, the largest share of scientific publications, more than one-third of scientific publications cited in patents, and world-class research universities (NRC, 2014).
There are numerous examples of government-funded research on environment and water resources that were funded to facilitate and enhance the solving of water and water management problems and also done to develop the scientific knowledge necessary to support undergird mandated regulatory programs. This research has led to significant payoffs for the nation or for distinct regions of the nation.
The federal government must fund the development of environmental models for understanding the physical, chemical, and biological processes and also for regulatory compliance. “Those who believe profit-driven companies will altruistically pay for basic science that has wide-ranging benefits—but mostly to others and not for a generation—are naïve” (Myhrvold, 2016).